Volume Based Technical Analysis

Using Volatility Analysis to predict Stock Market Crashes


"Technical analysis is not exact science" - you will find it in many references and this is correct. However, when it comes to the stock market trading we may say that nothing is an exact science and nothing guarantees future performance. Now matter what you use, either fundamental or technical analysis, there is never going to be 100% guarantee that future market or a stock's trend will perform as your predicted. All predictions are based on the analysis of the past. A fundamental analyst compares past trends to the past fundamental data by assuming that similar fundamental data in the future would lead to similar trend behavior. The same is done in technical analysis. In our case we attempted to take a look back in the past at market volatility data and compare it to market trend's changes in the past.

The one may assume that pattern between changes in volatility and changes in a price trend noted in the past would be the same in the future. However, "technical analysis is not an exact science" and if you make a decision to use this study's results in your own technical analysis you have to understand that you are doing it at your own risk. Also, you have to understand that this study is done on one index only. While principles of volatility/trend pattern mentioned below may remain similar, the numbers stated below will be different for other market indexes and other stocks.

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The goal of the following study was to confirm one of the postulates of technical analysis that volatility is higher during down-trend as traders are less confident in the future and volatility is lower during up-trend when traders are more confident in their investments.  Also, we attempted to find a pattern that may helps to predict stock market recessions, crashes and long-term down-trend. This study is based on the analysis of volatility on the daily charts (1-bar = 1 day) of the S&P 500 index.

We have selected the S&P 500 index because it reflects the stock market overall sentiment and by many analysts this index is considered to be much better gauge of the U.S. economy then DJI and other market indexes. Second point in the favor of the S&P 500 over stocks is that it allows us to track the history back to early 1980th. Plus we may disregard elements of fundamental analysis (which could be essential when a stock's trend reversals are analyzed) as it is already done by the Standards & Poors - the company that maintain the constituents of the S&P 500 index and calculates this index.

In our research we used Absolute ATR (ATR%) to evaluate the volatility. The Average True Range is well known in technical analysis as a perfect tool to evaluate volatility of a security. Choice was passed to Absolute ATR as it allows tracking the volatility in absolute values (in percent) which provide an ability of comparing volatility changes during different periods in history disregarding the price at which an analyzed instrument was traded. Such, in 1980th the S&P 500 was traded below $300 and in 2014 it was traded above $1,800 and Absolute Average True Range indicators lets us to compare volatility of this two periods in history.

We tested number of different settings starting daily charts (1 bar = 1 day) up to the weekly charts (1 bar = 5 trading days) with different ATR% bar period setting and we stopped our choice on the 14-day bar period for Average True Range because it reduces the spikes by keeping the lag relatively small. You will be able to find a chart setting which may predict the possibility of a stock market crash better (especially if you go to higher than 1-day charts), yet we kept our choice it because it will let you to verify our study results on charts easily and it is also mentioned in many resources as recommended ATR setting.

Click here for ATR history calculator or Indexes.

NOTE: You should know that whenever i this article we refer to the volatility we refer to the 14-day Absolute ATR applied to the S&P 500 index.

Our study is divided in four parts. In the first part we show you all occurrences of high volatility in the past. In the second part we discuss the volatility during the long-term up-trends. In the third summary part we gathered the main points that should be taken into the consideration when volatility is used in technical analysis of a long-term market trend.

Periods of High Volatility

In this part you will see S&P 500 charts of the periods of high volatility from the time of this study was performed (May of 2014) back to the early 1980th. As was already mentioned above, 14-day ATR% was used. Absolute ATR values at and above 2% were considered as indication of high volatility trading. Thus, in the periods of high volatility, we had in average 2% and higher price movements within 14 consecutive trading sessions.

NOTE: Whenever we refer to high volatility in this study we are referring to 14-day Absolute ATR readings at and above 2%. Whenever we refer to low volatility in this study, we refer to 14-day Absolute ATR readings below 2%.

Correction in August 2011

Chart #1: S&P 500 index in 2011.

Volatility chart during stock market correction in August 2011

Correction in May 2010

Chart #2: S&P 500 index in 2010.

The S&P 500 Volatility chart during the crash in may 2010

Stock market Crash in 2008

This stock market crash is known in history as the "Housing Market Bubble". It hit strongly big financial institutions and big auto-makers.

Chart #3: S&P 500 index in the beginning of 2008.

The S&P 500 Volatility chart during the begining of 2008 crash

Chart #4: S&P 500 index chart during the 2008 stock market crash.

Volatility during stock market correction in August 2011

Overall, the high volatility was noted far before the stock market crash - when the stock market went into deep correction in January 2008. After the bounce up the market (S&P 500 index) continued sliding down on low volatility until it finally crashed in September 2008. The market crash was quite strong and high volatility was still seen during the several months at the beginning of the recovery as well.

Stock market Crash in 2000 - 2003

This stock market crash is known in the history as "Internet Bubble".

Chart #5: S&P 500 index chart in 2000 just before the crash.

The S&P 500 index Volatility chart in 2000

Chart #6: S&P 500 index chart in 2001 - beginning of the crash.

High volatility readings on the S&P 500 index chart in 2001

Chart #7: The S&P 500 index chart in 2002 - the final stage of the market crash.

The S&P 500 index chart of the final stage of the 2000-2003 stock market crash

Overall, 2000-2003 recession was prolonged in time and during this recession we had strong bounces up. During this recession we had periods of high volatility (ATR > 2%) as well as periods of low volatility (ATR < 2%).

Correction in August 1998

Chart #8: The S&P 500 index chart of the deep correction in 1998.

The S&P 500 index chart in 1998

Stock Market Crash in 1997

Chart #9: The S&P 500 index chart in 1997.

S&P 500 index chart in 1997

Correction in August 1990

Chart #10: The S&P 500 index chart at the end of 1990.

The S&P 500 index chart during the deep correction at the end of 1990

Stock Market Crash in 1987

This stock market crash is known in the history as "Black Monday"

Chart #11: S&P 500 index chart of the "Black Monday" - market crash in 1987.

S&P 500 index chart of 1987 market crash

Low Volatility levels and long-term Uptrend

As a result of this study, it could be said that 14-day ATR% readings below 2% level could be considered as a sign of long term up-trend. Thus, low volatility was seen during the following Bullish periods (in the brackets you will see approximate S&P 500 index values at the beginning and end of these periods respectfully):

Total buy and hold S&P 500 index growth since 1987 crash until June 2014 (when this study was done) would be around 630%. On the other hand, compound profit from the caught by low volatility up-trends listed above would be around 1,600%. However, this number does not take into account periods of low volatility during the 2000-2003 and 2008 stock market crashes when the volatility level remained below 2% and S&P 500 index was in decline. In order to avoid these periods of low volatility during long-term down-trends, a trader or a technical analyst has to use other additional technical indicators or to implement an additional volatility rule which would state that if after recorded high volatility readings , volatility drops to low levels, however the market continues to decline it, could be a signal confirming a stock market crash and long-term bullish position should not be initiated.


You have to understand that this study was done on the S&P 500 index and the numbers (14-day Absolute ATR and 2% critical volatility level) mentioned in this study refer to the S&P 500 index only. If you analyze the DJI, Russell 2000, Nasdaq 100 or other indexes, you should perform research and find the volatility setting which would fit the indexes you analyze. As well, the volatility numbers mentioned here should not be applied to stocks. Each stock moves with different volatility.

Also, you should remember, that the goal of this study was to spot pattern in volatility that would help us to identify stock market crashes. If you want to use volatility in spotting market corrections, different volatility setting should be used.

As the result of our research we may say that for the S&P 500 index (pros and in green, cons are in red and statements just in black):

Several additional points noted during our research and not related analysis of long-term trends:

Example Of Long-Term Trading System

This is just an example of conservative long-term trading system that uses volatility to avoid trading during stock market crashes, long-term down-trends and recessions. In this example a hypothetical trader does not sell short - he only buys long or remain in cash. This system is for the S&P 500 index and when we refer to volatility we refer to 14-day ATR% applied to the S&P 500 index. Under high volatility levels we understand 14-day ATR% readings is at or above 2%. Respectfully, when we refer in this system to low volatility levels we are referring to the 14-day ATR readings below 2%

Rule #1: When volatility on the S&P 500 rises to high levels (at or above 2%), check when the last time high volatility on this index was recorded:

  1. If high volatility levels were also seen within the past six months, then exit long trade and remain in cash - the odds are high that this is long-term down trend.
  2. If previous high volatility trading was seen more than six month ago - the odds are good that this is just a deep correction. Still, depending on when it was and personal risk tolerance you may exit long trade or remain in long trade. As an example, if the last high volatility was seen two years ago, the odds are high that this is a deep correction and you may remain in long position. If it occurred eight months ago, a more conservative trader may exit a long position into a cash as the odds will be only slightly in the favor of deep correction over a recession.

Rule #2: When volatility on the S&P 500 rises to high levels (at or above 2%), check the news to understand the main cause of this decline and what affect on the market it may have.

Rule #3: 4% and higher volatility should be considered as a crash volatility.  No any long position should be open by that time.

Rule #4: When volatility on the S&P 500 drops to the low levels (below 2%) after being at high levels (at or above 2%) you may consider entering a long position:

System's disclaimer: One more time we would like to remind that the simple trading system described above is just an example. If you want to use this system you may use it at your own risk. If you want to adopt this system to other indexes or stocks it could be highly recommended scanning the history and finding appropriate volatility setting (ATR% bar period and critical volatility level)

Victor Kalitowski

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